Last chance! 50% off unlimited learning
Sale ends in
After all processing steps are done and before exporting as an SSN object measurements can be added to the site map. They can contain multiple parameters and repeated measurements at the same site.
merge_sites_measurements(measurements, site_id, all_sites = FALSE, ...)
character string, data.table or data.frame object; path to table data containing the data or a data.table or data.frame object
character string; columns name that gives the unique name of the site. Must be identical in both the sites vector object and the table of measurements
logical; should sites without measurements be preserved (default FALSE)
additional arguments to read.table in case measuremtes
is a file path
to table data; see read.table
for details.
Measurements are merged to the sites objects based on site_id
. If
there are repeated measurements, point features are duplicated and the 'pid' of the
sites is updated accordingly to be unique.
# NOT RUN {
dem_path <- system.file("extdata", "nc", "elev_ned_30m.tif", package = "openSTARS")
if(.Platform$OS.type == "windows"){
grass_program_path = "c:/Program Files/GRASS GIS 7.6"
} else {
grass_program_path = "/usr/lib/grass78/"
}
setup_grass_environment(dem = dem_path,
gisBase = grass_program_path,
remove_GISRC = TRUE,
override = TRUE
)
gmeta()
# Load files into GRASS
dem_path <- system.file("extdata", "nc", "elev_ned_30m.tif", package = "openSTARS")
sites_path <- system.file("extdata", "nc", "sites_nc.shp", package = "openSTARS")
import_data(dem = dem_path, sites = sites_path)
# Derive streams from DEM
derive_streams(burn = 0, accum_threshold = 700, condition = TRUE, clean = TRUE)
# Check and correct complex junctions (there are no complex confluences in this
# example date set)
cj <- check_compl_confluences()
if(cj){
correct_compl_confluences()
}
# Prepare edges
calc_edges()
# Prepare site
calc_sites()
merge_sites_measurements(measurements = system.file(
"extdata", "nc", "obs_data.csv", package = "openSTARS"),
site_id = "site_id", sep = ",", dec = ".")
# note the dublicated rows, and the new columns at the end
sites <- readVECT("sites", ignore.stderr = TRUE)
head(sites@data, n = 6)
# }
Run the code above in your browser using DataLab